mich0611's Projects
By using digital signal processing to eliminate unpleasing noise. Original sound - Lisa_noise.wav, the processed file - Processed_Lisa.wav.
🎮OmegaXYZ.com演化计算文章目录(实时更新)
game creation
Indicator-based Evolutionary Algorithm with Epsilon indicator
A framework for single/multi-objective optimization with metaheuristics
taking notes from codecademy learning
By using genetic algorithm to simulate lunarlander optimization.
Config files for my GitHub profile.
Q. Zhang and H. Li, MOEA/D: A Multi-objective Evolutionary Algorithm Based on Decomposition, IEEE Trans. on Evolutionary Computation, vol.11, no. 6, pp712-731
This is a python implementation of NSGA-II algorithm. NSGA is a popular non-domination based genetic algorithm for multi-objective optimization. It is a very effective algorithm but has been generally criticized for its computational complexity, lack of elitism and for choosing the optimal parameter value for sharing parameter σshare. A modified version, NSGA II was developed, which has a better sorting algorithm , incorporates elitism and no sharing parameter needs to be chosen a priori.
Nondominated sorting genetic algorithm
Implementation NSGA-II algorithm in form of python library
BFS, DFS, A*, and Uniform Cost Search Algorithms implemented for Pacman game
A python library for the following Multiobjective Optimization Algorithms or Many Objectives Optimization Algorithms: C-NSGA II; CTAEA; GrEA; HypE; IBEA-FC; IBEA-HV; MOEA/D; NAEMO; NSGA II; NSGA III; OMOPSO; PAES; RVEA; SMPSO; SMS-EMOA; SPEA2; U-NSGA III
HW assignment of RISC_V
Stacking Classifiers for Higher Predictive Performance